Transmission strategies for broadband wireless systems with MMSE turbo equalization

This monograph details efficient transmission strategies for single-carrier wireless broadband communication systems employing iterative (turbo) equalization. In particular, the first part focuses on the design and analysis of low complexity and robust MMSE-based turbo equalizers operating in the frequency domain. Accordingly, several novel receiver schemes are presented which improve the convergence properties and error performance over the existing turbo equalizers. The second part discusses concepts and algorithms that aim to increase the power and spectral efficiency of the communication system by efficiently exploiting the available resources at the transmitter side based upon the channel conditions. The challenging issue encountered in this context is how the transmission rate and power can be optimized, while a specific convergence constraint of the turbo equalizer is guaranteed.Die vorliegende Arbeit beschäftigt sich mit dem Entwurf und der Analyse von effizienten Übertragungs-konzepten für drahtlose, breitbandige Einträger-Kommunikationssysteme mit iterativer (Turbo-) Entzerrung und Kanaldekodierung. Dies beinhaltet einerseits die Entwicklung von empfängerseitigen Frequenzbereichs-entzerrern mit geringer Komplexität basierend auf dem Prinzip der Soft Interference Cancellation Minimum-Mean Squared-Error (SC-MMSE) Filterung und andererseits den Entwurf von senderseitigen Algorithmen, die durch Ausnutzung von Kanalzustandsinformationen die Bandbreiten- und Leistungseffizienz in Ein- und Mehrnutzersystemen mit Mehrfachantennen (sog. Multiple-Input Multiple-Output (MIMO)) verbessern. Im ersten Teil dieser Arbeit wird ein allgemeiner Ansatz für Verfahren zur Turbo-Entzerrung nach dem Prinzip der linearen MMSE-Schätzung, der nichtlinearen MMSE-Schätzung sowie der kombinierten MMSE- und Maximum-a-Posteriori (MAP)-Schätzung vorgestellt. In diesem Zusammenhang werden zwei neue Empfängerkonzepte, die eine Steigerung der Leistungsfähigkeit und Verbesserung der Konvergenz in Bezug auf existierende SC-MMSE Turbo-Entzerrer in verschiedenen Kanalumgebungen erzielen, eingeführt. Der erste Empfänger - PDA SC-MMSE - stellt eine Kombination aus dem Probabilistic-Data-Association (PDA) Ansatz und dem bekannten SC-MMSE Entzerrer dar. Im Gegensatz zum SC-MMSE nutzt der PDA SC-MMSE eine interne Entscheidungsrückführung, so dass zur Unterdrückung von Interferenzen neben den a priori Informationen der Kanaldekodierung auch weiche Entscheidungen der vorherigen Detektions-schritte berücksichtigt werden. Durch die zusätzlich interne Entscheidungsrückführung erzielt der PDA SC-MMSE einen wesentlichen Gewinn an Performance in räumlich unkorrelierten MIMO-Kanälen gegenüber dem SC-MMSE, ohne dabei die Komplexität des Entzerrers wesentlich zu erhöhen. Der zweite Empfänger - hybrid SC-MMSE - bildet eine Verknüpfung von gruppenbasierter SC-MMSE Frequenzbereichsfilterung und MAP-Detektion. Dieser Empfänger besitzt eine skalierbare Berechnungskomplexität und weist eine hohe Robustheit gegenüber räumlichen Korrelationen in MIMO-Kanälen auf. Die numerischen Ergebnisse von Simulationen basierend auf Messungen mit einem Channel-Sounder in Mehrnutzerkanälen mit starken räumlichen Korrelationen zeigen eindrucksvoll die Überlegenheit des hybriden SC-MMSE-Ansatzes gegenüber dem konventionellen SC-MMSE-basiertem Empfänger. Im zweiten Teil wird der Einfluss von System- und Kanalmodellparametern auf die Konvergenzeigenschaften der vorgestellten iterativen Empfänger mit Hilfe sogenannter Korrelationsdiagramme untersucht. Durch semi-analytische Berechnungen der Entzerrer- und Kanaldecoder-Korrelationsfunktionen wird eine einfache Berechnungsvorschrift zur Vorhersage der Bitfehlerwahrscheinlichkeit von SC-MMSE und PDA SC-MMSE Turbo Entzerrern für MIMO-Fadingkanäle entwickelt. Des Weiteren werden zwei Fehlerschranken für die Ausfallwahrscheinlichkeit der Empfänger vorgestellt. Die semi-analytische Methode und die abgeleiteten Fehlerschranken ermöglichen eine aufwandsgeringe Abschätzung sowie Optimierung der Leistungsfähigkeit des iterativen Systems. Im dritten und abschließenden Teil werden Strategien zur Raten- und Leistungszuweisung in Kommunikationssystemen mit konventionellen iterativen SC-MMSE Empfängern untersucht. Zunächst wird das Problem der Maximierung der instantanen Summendatenrate unter der Berücksichtigung der Konvergenz des iterativen Empfängers für einen Zweinutzerkanal mit fester Leistungsallokation betrachtet. Mit Hilfe des Flächentheorems von Extrinsic-Information-Transfer (EXIT)-Funktionen wird eine obere Schranke für die erreichbare Ratenregion hergeleitet. Auf Grundlage dieser Schranke wird ein einfacher Algorithmus entwickelt, der für jeden Nutzer aus einer Menge von vorgegebenen Kanalcodes mit verschiedenen Codierraten denjenigen auswählt, der den instantanen Datendurchsatz des Mehrnutzersystems verbessert. Neben der instantanen Ratenzuweisung wird auch ein ausfallbasierter Ansatz zur Ratenzuweisung entwickelt. Hierbei erfolgt die Auswahl der Kanalcodes für die Nutzer unter Berücksichtigung der Einhaltung einer bestimmten Ausfallwahrscheinlichkeit (outage probability) des iterativen Empfängers. Des Weiteren wird ein neues Entwurfskriterium für irreguläre Faltungscodes hergeleitet, das die Ausfallwahrscheinlichkeit von Turbo SC-MMSE Systemen verringert und somit die Zuverlässigkeit der Datenübertragung erhöht. Eine Reihe von Simulationsergebnissen von Kapazitäts- und Durchsatzberechnungen werden vorgestellt, die die Wirksamkeit der vorgeschlagenen Algorithmen und Optimierungsverfahren in Mehrnutzerkanälen belegen. Abschließend werden außerdem verschiedene Maßnahmen zur Minimierung der Sendeleistung in Einnutzersystemen mit senderseitiger Singular-Value-Decomposition (SVD)-basierter Vorcodierung untersucht. Es wird gezeigt, dass eine Methode, welche die Leistungspegel des Senders hinsichtlich der Bitfehlerrate des iterativen Empfängers optimiert, den konventionellen Verfahren zur Leistungszuweisung überlegen ist

Trickle-based interference cancellation schemes for CDMA systems

In this thesis, we introduce a novel approach to interference cancellation for code division multiple access uplink transmission. Several models combining principles of serial and parallel interference cancellation are discussed. The proposed scheme is derived from the analysis of these hybrid models and applies a user configuration algorithm (termed "trickle") in order to provide an improved bit-error-rate performance. The algorithm utilizes an adaptive matrix to compute the required configuration to be used for the subsequent interference cancellation stage. Bit-streaming, pipelined multiuser detection is employed and channel estimates are obtained using sample pilot data known at the receiver. We demonstrate that significant performance improvements can by achieved over various hybrid schemes. A reduced-complexity version of the trickle algorithm is also introduced where the processing delay is greatly reduced while maintaining similar performance. We present several numerical examples through which we demonstrate the efficacy of the proposed algorithms relative to existing interference cancellation algorithms

Symbol by Symbol Soft-Input Soft-Output Multiuser Detection for Frequency Selective Mimo Channels

We introduce a symbol by symbol, soft-input soft-output (SISO) multiuser detector for frequency selective multiple-input multiple-output (MIMO) channels. The basic principle of this algorithm is to extract a posteriori probabilities (APPs) of all interfering symbols at each symbol interval and then feed these updated APPs as a priori probabilities (apPs) for joint APP extraction in the next symbol interval. Unlike nearoptimal block oriented sphere decoding (SD) and soft decision equalization (SDE), the computational complexity of this updating APP (UA) algorithm is linear in the number of symbols but the exponential computational load of optimal joint APP extraction makes the basic UA impractical. To decrease computations we replace the optimal joint APP extractor by a groupwise SISO multiuser detector with a soft sphere decoding core. The resulting reduced complexity updating APP (RCUA) equalizer is flexible in different situations and outperforms the traditional sub-optimal MMSE-DFE without increasing the computational costs substantially

Transmit and receive techniques for MIMO-OFDM systems

Ph.DDOCTOR OF PHILOSOPH

Constrained Detection for Spatial-Multiplexing Multiple-Input–Multiple-Output Systems

A family of detectors that exploit signal constraints is developed for maximum-likelihood detection for multiple-input–multiple-output (MIMO) systems. Real constrained detectors and decision-feedback detectors are proposed for real constellations by forcing the relaxed solution to be real. A generalized minimum mean square error (GMMSE) and constrained least squares MIMO detectors are also developed for unitary and nonunitary signal constellations. Using these constrained detectors, we propose a new ordering scheme to achieve a tradeoff between interference suppression and noise enhancement. Moreover, to mitigate the inherent error propagation, the decision-feedback MIMO detectors are integrated with signal constraints. The simulation results show that our combined detector achieves a significant performance gain over vertical Bell Laboratories layered space-time (V-BLAST) detection

Application of integer quadratic programming in detection of high-dimensional wireless systems

High-dimensional wireless systems have recently generated a great deal of interest due to their ability to accommodate increasing demands for high transmission data rates with high communication reliability. Examples of such large-scale systems include single-input, single-output symbol spread OFDM system, large-scale single-user multi-input multi-output (MIMO) OFDM systems, and large-scale multiuser MIMO systems. In these systems, the number of symbols required to be jointly detected at the receiver is relatively large. The challenge with the practical realization of these systems is to design a detection scheme that provides high communication reliability with reasonable computational complexity, even as the number of simultaneously transmitted independent communication signals becomes very large.^ Most of the optimal or near-optimal detection techniques that have been proposed in the literature of relatively low-dimensional wireless systems, such as MIMO systems in which number of antennas is less than 10, become problematic for high-dimensional detection problems. That is, their performance degrades or the computational complexity becomes prohibitive, especially when higher-order QAM constellations are employed.^ In the first part of this thesis, we propose a near-optimal detection technique which offers a flexible trade-off between complexity and performance. The proposed technique formulates the detection problem in terms of Integer Quadratic Programming (IQP), which is then solved through a controlled Branch and Bound (BB) search tree algorithm. In addition to providing good performance, an important feature of this approach is that its computational complexity remains roughly the same even as we increase the constellation order from 4-QAM to 256-QAM. The performance of the proposed algorithm is investigated for both symbol spread OFDM systems and large-scale MIMO systems with both frequency selective and at fading channels.^ The second part of this work focuses on a reduced complexity version of IQP referred to as relaxed quadratic programming (QP). In particular, QP is used to reformulate two widely used detection schemes for MIMO OFDM: (1) Successive Interference Cancellation (SIC) and (2) Iterative Detecting and Decoding (IDD). First, SIC-based algorithms are derived via a QP formulation in contrast to using a linear MMSE detector at each stage. The resulting QP-SIC algorithms offer lower computational complexity than the SIC schemes that employ linear MMSE at each stage, especially when the dimension of the received signal vector is high. Three versions of QP-SIC are proposed based on various trade-offs between complexity and receiver performance; each of the three QP-SIC algorithms outperforms existing SIC techniques. Second, IDD-based algorithms are developed using a QP detector. We show how the soft information, in terms of the Log Likelihood Ratio (LLR), can be extracted from the QP detector. Further, the procedure for incorporating the a-priori information that is passed from the channel decoder to the QP detector is developed. Simulation results are presented demonstrating that the use of QP in IDD offers improved performance at the cost of a reasonable increase in complexity compared to linear detectors

Blind source separation for interference cancellation in CDMA systems

Communication is the science of "reliable" transfer of information between two parties, in the sense that the information reaches the intended party with as few errors as possible. Modern wireless systems have many interfering sources that hinder reliable communication. The performance of receivers severely deteriorates in the presence of unknown or unaccounted interference. The goal of a receiver is then to combat these sources of interference in a robust manner while trying to optimize the trade-off between gain and computational complexity. Conventional methods mitigate these sources of interference by taking into account all available information and at times seeking additional information e.g., channel characteristics, direction of arrival, etc. This usually costs bandwidth. This thesis examines the issue of developing mitigating algorithms that utilize as little as possible or no prior information about the nature of the interference. These methods are either semi-blind, in the former case, or blind in the latter case. Blind source separation (BSS) involves solving a source separation problem with very little prior information. A popular framework for solving the BSS problem is independent component analysis (ICA). This thesis combines techniques of ICA with conventional signal detection to cancel out unaccounted sources of interference. Combining an ICA element to standard techniques enables a robust and computationally efficient structure. This thesis proposes switching techniques based on BSS/ICA effectively to combat interference. Additionally, a structure based on a generalized framework termed as denoising source separation (DSS) is presented. In cases where more information is known about the nature of interference, it is natural to incorporate this knowledge in the separation process, so finally this thesis looks at the issue of using some prior knowledge in these techniques. In the simple case, the advantage of using priors should at least lead to faster algorithms.reviewe

High capacity multiuser multiantenna communication techniques

One of the main issues involved in the development of future wireless communication systems is the multiple access technique used to efficiently share the available spectrum among users. In rich multipath environment, spatial dimension can be exploited to meet the increasing number of users and their demands without consuming extra bandwidth and power. Therefore, it is utilized in the multiple-input multiple-output (MIMO) technology to increase the spectral efficiency significantly. However, multiuser MIMO (MU-MIMO) systems are still challenging to be widely adopted in next generation standards. In this thesis, new techniques are proposed to increase the channel and user capacity and improve the error performance of MU-MIMO over Rayleigh fading channel environment. For realistic system design and performance evaluation, channel correlation is considered as one of the main channel impurities due its severe influence on capacity and reliability. Two simple methods called generalized successive coloring technique (GSCT) and generalized iterative coloring technique (GICT) are proposed for accurate generation of correlated Rayleigh fading channels (CRFC). They are designed to overcome the shortcomings of existing methods by avoiding factorization of desired covariance matrix of the Gaussian samples. The superiority of these techniques is demonstrated by extensive simulations of different practical system scenarios. To mitigate the effects of channel correlations, a novel constellation constrained MU-MIMO (CC-MU-MIMO) scheme is proposed using transmit signal design and maximum likelihood joint detection (MLJD) at the receiver. It is designed to maximize the channel capacity and error performance based on principles of maximizing the minimum Euclidean distance (dmin) of composite received signals. Two signal design methods named as unequal power allocation (UPA) and rotation constellation (RC) are utilized to resolve the detection ambiguity caused by correlation. Extensive analysis and simulations demonstrate the effectiveness of considered scheme compared with conventional MU-MIMO. Furthermore, significant gain in SNR is achieved particularly in moderate to high correlations which have direct impact to maintain high user capacity. A new efficient receive antenna selection (RAS) technique referred to as phase difference based selection (PDBS) is proposed for single and multiuser MIMO systems to maximize the capacity over CRFC. It utilizes the received signal constellation to select the subset of antennas with highest (dmin) constellations due to its direct impact on the capacity and BER performance. A low complexity algorithm is designed by employing the Euclidean norm of channel matrix rows with their corresponding phase differences. Capacity analysis and simulation results show that PDBS outperforms norm based selection (NBS) and near to optimal selection (OS) for all correlation and SNR values. This technique provides fast RAS to capture most of the gains promised by multiantenna systems over different channel conditions. Finally, novel group layered MU-MIMO (GL-MU-MIMO) scheme is introduced to exploit the available spectrum for higher user capacity with affordable complexity. It takes the advantages of spatial difference among users and power control at base station to increase the number of users beyond the available number of RF chains. It is achieved by dividing the users into two groups according to their received power, high power group (HPG) and low power group (LPG). Different configurations of low complexity group layered multiuser detection (GL-MUD) and group power allocation ratio (η) are utilized to provide a valuable tradeoff between complexity and overall system performance. Furthermore, RAS diversity is incorporated by using NBS and a new selection algorithm called HPG-PDBS to increase the channel capacity and enhance the error performance. Extensive analysis and simulations demonstrate the superiority of proposed scheme compared with conventional MU-MIMO. By using appropriate value of (η), it shows higher sum rate capacity and substantial increase in the user capacity up to two-fold at target BER and SNR values

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems